1. Field of the Invention
The present invention relates to a similar semicircle detecting apparatus that detects a similar semicircular shape similar to a semicircular shape from an image represented by pixels that are two-dimensionally arranged, and a computer-readable storage medium storing a similar semicircle detecting program that causes a computer to operate as the similar semicircle detecting apparatus.
2. Description of the Related Art
Conventionally, security cameras are disposed in convenience stores or banks as one of security countermeasures. Moving pictures that are photographed by the security cameras are displayed on a display screen of a monitoring room or the like and are recorded. The moving pictures are used to specify a criminal when a crime is committed.
Moving pictures that are photographed by the security cameras are recorded as analog data, conventionally. However, in recent years, the moving pictures are recorded as digital data, for convenience of management and the like. In addition, in the security cameras that have the utilization objects described above, the moving pictures that are photographed over a long period of time need to be recorded, but there is a limitation in a recording capacity of a recording device that records the moving pictures. For this reason, when the moving pictures are recorded, a compressing process is applied to the moving pictures. Meanwhile, if the compressing process is applied to the moving pictures, the moving pictures may become unclear. If the moving pictures become unclear, it may be difficult to grasp an accurate occurrence situation of an event or specify a person from the moving pictures.
In recent years, in a field of an imaging apparatus that lays stress on a digital camera, with the development of a hardware technique of the imaging apparatus, a software technique of the imaging apparatus has been developed. One example of the software technique is a technique for detecting a face portion of a person in an angle of view, that is, a so-called face detecting technique. In the face detecting technique, generally, face parts, such as eyes, a nose, and a mouth, which become markers of the face portion in the angle of view, are detected, and the face portion in the angle of view is detected on the basis of the detected face parts.
When the face detecting technique is applied to the security camera, it is possible to detect a face portion of a person in an angle of view, when the moving pictures are taken. In addition, when the moving pictures are recorded, a high compressing process can be applied to only an area other than the detected face portion. As a result, the security camera is considered to be obtained, in which the face portion of the person in the recorded moving pictures becomes clear, and a person who turns a front surface with respect to the security camera can be easily specified.
Here, in order to effectively use the moving pictures that are taken by the security cameras to specify the person, it is important that when the person who turns a front surface with respect to the security camera can be easily specified and it is also important that when the person who turns a side surface or a back surface with respect to the security camera can be easily specified. For this reason, in addition to the face portion of the person, that is, the front surface of the person, and the head portion of the person including the front surface, the side surface, and the back surface of the person need to be detected. If the head portion can be detected in the moving pictures, the detected head portion can be traced in the angle of view, and can be effectively used to specify the person. However, the face detecting technique is a technique for detecting the face portion in the angle of view on the basis of the detected face parts. Accordingly, even though the face detecting technique is applied, it is difficult to detect a side surface or a back surface of a person who has a small amount of features in face portions, such as eyes, a nose, and a mouth, which become markers of the face portion.
In addition, conventionally, various techniques that detect a similar circular shape having a rounded outline using a point concentration filter to evaluate concentration degree of a gradient vectors in a peripheral area of a pixel in interest have been suggested (for example, see Wei et al., Characteristic Analysis of Point Concentricity Filter of Gradient Vector, “The Institute of Electronics, Information and Communication Engineers (IEICE) Trans. D-II Vol. J84-D-II No. 7”, July, 2001, p. 1289-1298 and Junichi Hasegawa et al., Automatic Extraction of Cancer Lesion Portion accompanied by Fold Concentration in Double Contrast Gastrography X-ray Image, “IEICE Trans. D-II Vol. J73-D-II No. 4”, April, 1990, p. 661-669).
The techniques that detect the similar circular shape using the point concentration filter are techniques that calculate a gradient direction where a characteristic amount, such as a luminance value or a chromaticity value in an image, varies, for each of plural evaluation pixels that are arranged along a circle using a predetermined pixel in interest as its center and surround the predetermined pixel in interest, calculate a pixel evaluation value based on an angle that is formed by a direction in which the evaluation pixel and the pixel in interest are connected and a gradient direction, for each of the plural evaluation pixels, and evaluate whether the evaluation pixels are pixels on a circle using the pixel in interest as its center on the basis of the calculated pixel evaluation values so as to detect the similar circular shape.
In addition, since the techniques that detect the similar circular shape using the point concentration filter are techniques that principally function even though the contrast between the similar circular shape as a detection object and a background of the similar circular shape is extraordinarily low, the techniques have been put to practical use in a field of medical image processing like automatic tumor detection that detects an abnormal shadow such as a cancer region having a similar circular shape from an X-ray image or a CT image.
Here, the outline of an upper portion of a head portion of a person has a similar semicircular shape that is similar to a semicircular shape. For this reason, it is anticipated that detection of a similar semicircular shape in an angle of view when a dynamic picture image is photographed is effectively used when the head portion of the person in an angle of view is detected.
However, as described above, the suggested techniques, in Wei et al., Characteristic Analysis of Point Concentricity Filter of Gradient Vector, “The Institute of Electronics, Information and Communication Engineers (IEICE) Trans. D-II Vol. J84-D-II No. 7”, July, 2001, p. 1289-1298 and Junichi Hasegawa et al., Automatic Extraction of Cancer Lesion Portion accompanied by Fold Concentration in Double Contrast Gastrography X-ray Image, “IEICE Trans. D-II Vol. J73-D-II No. 4”, April, 1990, p. 661-669, that detect the similar circular shape using the point concentration filter are techniques that evaluate whether the evaluation pixels are pixels on the circle using the pixel in interest as its center on the basis of the calculated pixel evaluation values and detect the similar circular shape. Accordingly, the suggested techniques cannot be directly used when the similar semicircular shape is detected.
Further, when the head portion of the person in the angle of view is detected on the basis of detection of the similar semicircular shape, a slope of the similar semicircular shape, that is, a slope of the head portion is very important information in a human body posture analysis. However, the slope of the similar circular shape cannot be obtained by the suggested techniques in Wei et al., Characteristic Analysis of Point Concentricity Filter of Gradient Vector, “The Institute of Electronics, Information and Communication Engineers (IEICE) Trans. D-II Vol. J84-D-II No. 7”, July, 2001, p. 1289-1298 and Junichi Hasegawa et al., Automatic Extraction of Cancer Lesion Portion accompanied by Fold Concentration in Double Contrast Gastrography X-ray Image, “IEICE Trans. D-II Vol. J73-D-II No. 4”, April, 1990, p. 661-669.